AIMC Topic: Machine Learning

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Artificial Intelligence-Enabled ECG: a Modern Lens on an Old Technology.

Current cardiology reports
PURPOSE OF REVIEW: To (i) review the concept of artificial intelligence (AI); (ii) summarize recent developments in artificial intelligence-enabled electrocardiogram (AI-ECG); (iii) address notable inherent limitations and challenges of AI-ECG; and (...

Serum adipokines/related inflammatory factors and ratios as predictors of infrapatellar fat pad volume in osteoarthritis: Applying comprehensive machine learning approaches.

Scientific reports
OBJECTIVE: The infrapatellar fat pad (IPFP) has been associated with knee osteoarthritis onset and progression. This study uses machine learning (ML) approaches to predict serum levels of some adipokines/related inflammatory factors and their ratios ...

Computer-aided therapeutic diagnosis for anorexia.

Biomedical engineering online
BACKGROUND: Anorexia nervosa is a clinical disorder syndrome of the wide spectrum without a fully recognized etiology. The necessary issue in the clinical diagnostic process is to detect the causes of this disease (e.g., my body image, food, family, ...

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

PLoS medicine
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible dama...

Machine learning and natural language processing methods to identify ischemic stroke, acuity and location from radiology reports.

PloS one
Accurate, automated extraction of clinical stroke information from unstructured text has several important applications. ICD-9/10 codes can misclassify ischemic stroke events and do not distinguish acuity or location. Expeditious, accurate data extra...

Exploring the mechanism of TCM formulae in the treatment of different types of coronary heart disease by network pharmacology and machining learning.

Pharmacological research
Traditional Chinese medicine (TCM) has long been used in the clinical treatment of coronary heart disease (CHD). TCM is characterized by syndrome-based medication, which is, using different TCM formulae for different syndromes. However, the underlyin...

Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology.

EBioMedicine
BACKGROUND: Adverse drug reactions (ADRs) are one of the leading causes of morbidity and mortality in health care. Understanding which drug targets are linked to ADRs can lead to the development of safer medicines.

How Will Machine Learning Inform the Clinical Care of Atrial Fibrillation?

Circulation research
Machine learning applications in cardiology have rapidly evolved in the past decade. With the availability of machine learning tools coupled with vast data sources, the management of atrial fibrillation (AF), a common chronic disease with significant...

A Multi-Objective Approach for Optimal Energy Management in Smart Home Using the Reinforcement Learning.

Sensors (Basel, Switzerland)
Maintaining a fair use of energy consumption in smart homes with many household appliances requires sophisticated algorithms working together in real time. Similarly, choosing a proper schedule for appliances operation can be used to reduce inappropr...